Articles | Volume 16, issue 22
https://doi.org/10.5194/gmd-16-6833-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-6833-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
24 Nov 2023
Model evaluation paper |
| 24 Nov 2023
| 24 Nov 2023
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 2: Influence of uncertainty factors
Wenxing Jia
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Xiaoye Zhang
CORRESPONDING AUTHOR
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Center for Excellence in Regional Atmospheric Environment, IUE, Chinese Academy of Sciences, Xiamen, 361021, China
Hong Wang
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Yaqiang Wang
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Deying Wang
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Junting Zhong
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Wenjie Zhang
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Lei Zhang
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Lifeng Guo
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Yadong Lei
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Jizhi Wang
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Yuanqin Yang
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Yi Lin
Key Laboratory for Mesoscale Severe Weather, Ministry of Education, and School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
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Ke Gui, Huizheng Che, Yu Zheng, Hujia Zhao, Wenrui Yao, Lei Li, Lei Zhang, Hong Wang, Yaqiang Wang, and Xiaoye Zhang
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This study utilized the globally gridded aerosol extinction data from CALIOP during 2007–2019 to investigate the 3D climatology, trends, and meteorological drivers of tropospheric type-dependent aerosols. Results revealed that the planetary boundary layer (PBL) and the free troposphere contribute 62.08 % and 37.92 %, respectively, of the global tropospheric TAOD. Trends in
CALIOP-derived aerosol loading, in particular those partitioned in the PBL, can be explained to a large extent by meteorology.
Hongyi Ding, Le Cao, Haimei Jiang, Wenxing Jia, Yong Chen, and Junling An
Geosci. Model Dev., 14, 6135–6153, https://doi.org/10.5194/gmd-14-6135-2021, https://doi.org/10.5194/gmd-14-6135-2021, 2021
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We performed a WRF model study to figure out the mechanism of how the change in minimum eddy diffusivity (Kzmin) in the planetary boundary layer (PBL) closure scheme (ACM2) affects the simulated near-surface temperature in Beijing, China. Moreover, the influence of changing Kzmin on the temperature prediction in areas with different land-use categories was studied. The model performance using a functional-type Kzmin for capturing the temperature change in this area was also clarified.
Yadong Lei, Xu Yue, Hong Liao, Lin Zhang, Yang Yang, Hao Zhou, Chenguang Tian, Cheng Gong, Yimian Ma, Lan Gao, and Yang Cao
Atmos. Chem. Phys., 21, 11531–11543, https://doi.org/10.5194/acp-21-11531-2021, https://doi.org/10.5194/acp-21-11531-2021, 2021
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We present the first estimate of ozone enhancement by fire emissions through ozone–vegetation interactions using a fully coupled chemistry–vegetation model (GC-YIBs). In fire-prone areas, fire-induced ozone causes a positive feedback to surface ozone mainly because of the inhibition effects on stomatal conductance.
Qingyang Xiao, Yixuan Zheng, Guannan Geng, Cuihong Chen, Xiaomeng Huang, Huizheng Che, Xiaoye Zhang, Kebin He, and Qiang Zhang
Atmos. Chem. Phys., 21, 9475–9496, https://doi.org/10.5194/acp-21-9475-2021, https://doi.org/10.5194/acp-21-9475-2021, 2021
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We used both statistical methods and a chemical transport model to assess the contribution of meteorology and emissions to PM2.5 during 2000–2018. Both methods revealed that emissions dominated the long-term PM2.5 trend with notable meteorological effects ranged up to 37.9 % of regional annual average PM2.5. The meteorological contribution became more beneficial to PM2.5 control in southern China but more unfavorable in northern China during the studied period.
Xiaojing Shen, Junying Sun, Fangqun Yu, Ying Wang, Junting Zhong, Yangmei Zhang, Xinyao Hu, Can Xia, Sinan Zhang, and Xiaoye Zhang
Atmos. Chem. Phys., 21, 7039–7052, https://doi.org/10.5194/acp-21-7039-2021, https://doi.org/10.5194/acp-21-7039-2021, 2021
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In this work, we revealed the changes of PNSD and NPF events during the COVID-19 lockdown period in Beijing, China, to illustrate the impact of reduced primary emission and elavated atmospheric oxidized capicity on the nucleation and growth processes. The subsequent growth of nucleated particles and their contribution to the aerosol pollution formation were also explored, to highlight the necessity of controlling the nanoparticles in the future air quality management.
Linlin Liang, Guenter Engling, Chang Liu, Wanyun Xu, Xuyan Liu, Yuan Cheng, Zhenyu Du, Gen Zhang, Junying Sun, and Xiaoye Zhang
Atmos. Chem. Phys., 21, 3181–3192, https://doi.org/10.5194/acp-21-3181-2021, https://doi.org/10.5194/acp-21-3181-2021, 2021
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A unique episode with extreme biomass burning (BB) impact, with daily concentration of levoglucosan as high as 4.37 µg m-3, was captured at an area upwind of Beijing. How this extreme BB pollution event was generated and what were the chemical properties of PM2.5 under this kind severe BB pollution level in the real atmospheric environment were both presented in this measurement report. Moreover, the variation of the ratios of BB tracers during different BB pollution periods was also exhibited.
Sunling Gong, Hongli Liu, Bihui Zhang, Jianjun He, Hengde Zhang, Yaqiang Wang, Shuxiao Wang, Lei Zhang, and Jie Wang
Atmos. Chem. Phys., 21, 2999–3013, https://doi.org/10.5194/acp-21-2999-2021, https://doi.org/10.5194/acp-21-2999-2021, 2021
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Surface concentrations of PM2.5 in China have had a declining trend since 2013 across the country. This research found that the control measures of emission reduction are the dominant factors in the PM2.5 declining trends in various regions. The contribution by the meteorology to the surface PM2.5 concentrations from 2013 to 2019 was not found to show a consistent trend, fluctuating positively or negatively by about 5% on the annual average and 10–20% for the fall–winter heavy-pollution seasons.
Lei Zhang, Sunling Gong, Tianliang Zhao, Chunhong Zhou, Yuesi Wang, Jiawei Li, Dongsheng Ji, Jianjun He, Hongli Liu, Ke Gui, Xiaomei Guo, Jinhui Gao, Yunpeng Shan, Hong Wang, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 14, 703–718, https://doi.org/10.5194/gmd-14-703-2021, https://doi.org/10.5194/gmd-14-703-2021, 2021
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Development of chemical transport models with advanced physics and chemical schemes is important for improving air-quality forecasts. This study develops the chemical module CUACE by updating with a new particle dry deposition scheme and adding heterogenous chemical reactions and couples it with the WRF model. The coupled model (WRF/CUACE) was able to capture well the variations of PM2.5, O3, NO2, and secondary inorganic aerosols in eastern China.
Yucong Miao, Huizheng Che, Xiaoye Zhang, and Shuhua Liu
Atmos. Chem. Phys., 20, 5899–5909, https://doi.org/10.5194/acp-20-5899-2020, https://doi.org/10.5194/acp-20-5899-2020, 2020
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By combining long-term observational data analyses, synoptic classifications, and meteorology–chemistry coupled simulations, the complicated impacts of large-scale synoptic forcing and local boundary layer processes on the aerosol pollution in the Beijing–Tianjin–Hebei region have been investigated. The influences of the aerosol radiative effect on boundary layer structure and pollution were also examined. This study has important implications for better understanding pollution in China.
Cheng Gong, Yadong Lei, Yimian Ma, Xu Yue, and Hong Liao
Atmos. Chem. Phys., 20, 3841–3857, https://doi.org/10.5194/acp-20-3841-2020, https://doi.org/10.5194/acp-20-3841-2020, 2020
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We evaluate ozone–vegetation feedback using a fully coupled chemistry–carbon–climate global model (ModelE2-YIBs). Ozone damage to photosynthesis, stomatal conductance, and isoprene emissions parameterized by different schemes and sensitivities is jointly considered. In general, surface ozone concentrations are increased due to ozone–vegetation interactions, especially over the regions with a high ambient ozone level such as the eastern US, eastern China, and western Europe.
Yadong Lei, Xu Yue, Hong Liao, Cheng Gong, and Lin Zhang
Geosci. Model Dev., 13, 1137–1153, https://doi.org/10.5194/gmd-13-1137-2020, https://doi.org/10.5194/gmd-13-1137-2020, 2020
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We coupled a dynamic vegetation model YIBs with the chemical transport model GEOS-Chem to develop a new tool for studying interactions between atmospheric chemistry and biosphere. Within this framework, leaf area index and stomatal conductance are predicted for chemical simulations. In turn, surface ozone causes negative impacts to plant growth and the consequent dry deposition. Such interactions are important for air pollution prediction but ignored in most of current chemical models.
Linlin Liang, Guenter Engling, Chang Liu, Wanyun Xu, Xuyan Liu, Yuan Cheng, Zhenyu Du, Gen Zhang, Junying Sun, and Xiaoye Zhang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-19, https://doi.org/10.5194/acp-2020-19, 2020
Revised manuscript not accepted
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Our study captured an episode with extreme biomass burning tracer level at an agricultural site in North China, with concentrations of levoglucosan as high as 4.37 μg m−3. Based on comparison of the chemical composition between different biomass burning periods, it appeared that biomass burning can obviously elevate the levels of organic components, but seems to have no significant effect on the production of secondary inorganic ions, although their precursors increased during the episode.
Renmin Yuan, Xiaoye Zhang, Hao Liu, Yu Gui, Bohao Shao, Xiaoping Tao, Yaqiang Wang, Junting Zhong, Yubin Li, and Zhiqiu Gao
Atmos. Chem. Phys., 19, 12857–12874, https://doi.org/10.5194/acp-19-12857-2019, https://doi.org/10.5194/acp-19-12857-2019, 2019
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To understand the contribution of ground emission during heavy pollution in Beijing, Tianjin and Hebei, aerosol fluxes were estimated in Beijing and Gucheng areas. The results show that in the three stages of a heavy pollution process (transport, accumulative and removal stages: TS, AS and RS), the ground emissions in the TS and RS stages are stronger, while the ground discharge in the AS stage is weak. The weakened mass flux indicates that the already weak turbulence would be further weakened.
Huizheng Che, Xiangao Xia, Hujia Zhao, Oleg Dubovik, Brent N. Holben, Philippe Goloub, Emilio Cuevas-Agulló, Victor Estelles, Yaqiang Wang, Jun Zhu, Bing Qi, Wei Gong, Honglong Yang, Renjian Zhang, Leiku Yang, Jing Chen, Hong Wang, Yu Zheng, Ke Gui, Xiaochun Zhang, and Xiaoye Zhang
Atmos. Chem. Phys., 19, 11843–11864, https://doi.org/10.5194/acp-19-11843-2019, https://doi.org/10.5194/acp-19-11843-2019, 2019
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A full-scale description of ground-based aerosol microphysical and optical properties over China is presented. Moreover, the results have also provided significant information about optical and radiative aerosol properties for different types of sites covering a broad expanse of China. The results have considerable value for ground-truthing satellite observations and validating aerosol models.
Xianyi Yang, Huizheng Che, Hitoshi Irie, Quanliang Chen, Ke Gui, Ying Cai, Yu Zheng, Linchang An, Hujia Zhao, Lei Li, Yuanxin Liang, Yaqiang Wang, Hong Wang, and Xiaoye Zhang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-339, https://doi.org/10.5194/amt-2019-339, 2019
Preprint withdrawn
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This study assesses the performance of SKYNET in comparison to AERONET (Aerosol Robotic Network) for retrieving aerosol optical properties (AOPs) in Beijing, China. SKYNET data retrieved by SR-CEReS analysis package are used to analyze a serious pollution event in winter over Beijing. The AOPs under three weather conditions (clean, dusty, haze) in Beijing are discussed. Measurements from the SKYNET skyradiometer can be used to analyze the AOPs over Beijing reasonably.
Huizheng Che, Ke Gui, Xiangao Xia, Yaqiang Wang, Brent N. Holben, Philippe Goloub, Emilio Cuevas-Agulló, Hong Wang, Yu Zheng, Hujia Zhao, and Xiaoye Zhang
Atmos. Chem. Phys., 19, 10497–10523, https://doi.org/10.5194/acp-19-10497-2019, https://doi.org/10.5194/acp-19-10497-2019, 2019
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A comprehensive assessment of the global and regional AOD trends over the past 37 years (1980–2016) is presented. AOD observations from both AERONET and CARSNET were used for the first time to assess the performance of the MERRA-2 AOD dataset on a global scale. Based on statistical models, we found the meteorological parameters explained a larger proportion of the regional AOD variability (20.4 %–2.8 %) when compared with emission factors (0 %%–56 %).
Hua Yu, Weijun Li, Yangmei Zhang, Peter Tunved, Manuel Dall'Osto, Xiaojing Shen, Junying Sun, Xiaoye Zhang, Jianchao Zhang, and Zongbo Shi
Atmos. Chem. Phys., 19, 10433–10446, https://doi.org/10.5194/acp-19-10433-2019, https://doi.org/10.5194/acp-19-10433-2019, 2019
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Interaction of anthropogenic particles with radiation and clouds plays an important role in Arctic climate change. The mixing state of different aerosols is a key parameter influencing such interactions. However, little is known of this parameter, preventing an accurate representation of this information in global models. Multi-microscopic techniques were used to find one general core–shell structure in which secondary sulfate particles were covered by organic coating in the Arctic atmosphere.
Weijun Li, Lei Liu, Qi Yuan, Liang Xu, Yanhong Zhu, Bingbing Wang, Hua Yu, Xiaokun Ding, Jian Zhang, Dao Huang, Dantong Liu, Wei Hu, Daizhou Zhang, Pingqing Fu, Maosheng Yao, Min Hu, Xiaoye Zhang, and Zongbo Shi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-539, https://doi.org/10.5194/acp-2019-539, 2019
Preprint withdrawn
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The real state of individual primary biological aerosol particles (PBAPs) derived from natural sources is under mystery, although many studies well evaluate the morphology, mixing state, and elemental composition of anthropogenic particles. It induces that some studies mislead some anthropogenic particles into biological particles through electron microscopy. Here we firstly estimate the full database of individual PBAPs through two microscopic instruments. The database is good for research.
Linlin Wang, Junkai Liu, Zhiqiu Gao, Yubin Li, Meng Huang, Sihui Fan, Xiaoye Zhang, Yuanjian Yang, Shiguang Miao, Han Zou, Yele Sun, Yong Chen, and Ting Yang
Atmos. Chem. Phys., 19, 6949–6967, https://doi.org/10.5194/acp-19-6949-2019, https://doi.org/10.5194/acp-19-6949-2019, 2019
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Urban boundary layer (UBL) affects the physical and chemical processes of the pollutants, and UBL structure can also be altered by pollutants. This paper presents the interactions between air pollution and the UBL structure by using the field data mainly collected from a 325 m meteorology tower, as well as from a Doppler wind lidar, during a severe heavy pollution event that occurred during 1–4 December 2016 in Beijing.
Junting Zhong, Xiaoye Zhang, Yaqiang Wang, Jizhi Wang, Xiaojing Shen, Hongsheng Zhang, Tijian Wang, Zhouqing Xie, Cheng Liu, Hengde Zhang, Tianliang Zhao, Junying Sun, Shaojia Fan, Zhiqiu Gao, Yubin Li, and Linlin Wang
Atmos. Chem. Phys., 19, 3287–3306, https://doi.org/10.5194/acp-19-3287-2019, https://doi.org/10.5194/acp-19-3287-2019, 2019
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In various haze regions in China, including the Guanzhong Plain, the middle and lower reaches of the Yangtze River, the Pearl River Delta, the Sichuan Basin, and the Northeast China Plain, heavy aerosol pollution episodes include inter-/trans-regional transport stages and cumulative stages (CSs). During CSs a two-way feedback mechanism exists between unfavorable meteorological conditions and cumulative aerosol pollution. This two-way feedback is further quantified and its magnitude is compared.
Angela Benedetti, Francesca Di Giuseppe, Luke Jones, Vincent-Henri Peuch, Samuel Rémy, and Xiaoye Zhang
Atmos. Chem. Phys., 19, 987–998, https://doi.org/10.5194/acp-19-987-2019, https://doi.org/10.5194/acp-19-987-2019, 2019
Hong Wang, Yue Peng, Xiaoye Zhang, Hongli Liu, Meng Zhang, Huizheng Che, Yanli Cheng, and Yu Zheng
Atmos. Chem. Phys., 18, 17717–17733, https://doi.org/10.5194/acp-18-17717-2018, https://doi.org/10.5194/acp-18-17717-2018, 2018
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The explosive growth (EG) of PM2.5 resulted in a PM2.5 maximum, which was generally underestimated by atmospheric chemical models due to the deficient description of the local
turbulence intermittent. The aerosol–radiation feedback (AF) and decrease in turbulence diffusion (DTD) may reduce the underestimation of PM2.5 EG by 20–25% and 14–20%, respectively. The modeled EG stage PM2.5 error was decreased from −40 to −51% to −11 to 2% by the combined effects of AF and DTD in Jing–Jin–Ji.
Yue Peng, Hong Wang, Yubin Li, Changwei Liu, Tianliang Zhao, Xiaoye Zhang, Zhiqiu Gao, Tong Jiang, Huizheng Che, and Meng Zhang
Atmos. Chem. Phys., 18, 17421–17435, https://doi.org/10.5194/acp-18-17421-2018, https://doi.org/10.5194/acp-18-17421-2018, 2018
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Two surface layer schemes are evaluated in eastern China based on observational flux data. The results indicate that the Li scheme better describes regional atmosphere stratification compared with the MM5 scheme, especially for the transition stage from unstable to stable atmosphere conditions, corresponding to PM2.5 accumulation. Our research suggests the potential improved possibilities for severe haze prediction in eastern China by coupling Li online into atmosphere chemical models.
Xiaoye Zhang, Junting Zhong, Jizhi Wang, Yaqiang Wang, and Yanju Liu
Atmos. Chem. Phys., 18, 5991–5999, https://doi.org/10.5194/acp-18-5991-2018, https://doi.org/10.5194/acp-18-5991-2018, 2018
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The relation between interdecadal changes in weather conditions and climate warming is uncertain. Here, the decadal worsening of meteorological conditions since the 1960s in the Beijing area was found to be partly attributed to climate warming, which is defined by more warming in the higher layers of the boundary layer (BL) than the lower layers. This worsening may also partly be related to the impact on the increasing aerosol pollution (particularly after 2010).
Tianze Sun, Huizheng Che, Bing Qi, Yaqiang Wang, Yunsheng Dong, Xiangao Xia, Hong Wang, Ke Gui, Yu Zheng, Hujia Zhao, Qianli Ma, Rongguang Du, and Xiaoye Zhang
Atmos. Chem. Phys., 18, 2949–2971, https://doi.org/10.5194/acp-18-2949-2018, https://doi.org/10.5194/acp-18-2949-2018, 2018
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The Yangtze River Delta (YRD) region is a key hub in China with air pollution problems. We applied various data from observations and satellites, finding particles in summer prefer hygroscopic growth leading to high scatter. Transported scatter particles lead to a cooling effect which lowers the boundary layer, creating positive feedback. Transported pollutants over YRD are from the North China Plain, northwestern deserts, and southern biomass burning. This finding helps air quality control.
Xiaojing Shen, Junying Sun, Niku Kivekäs, Adam Kristensson, Xiaoye Zhang, Yangmei Zhang, Lu Zhang, Ruxia Fan, Xuefei Qi, Qianli Ma, and Huaigang Zhou
Atmos. Chem. Phys., 18, 587–599, https://doi.org/10.5194/acp-18-587-2018, https://doi.org/10.5194/acp-18-587-2018, 2018
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In this study we used the NanoMap method by applying back trajectories and particle number size distribution in different rural sites in China to evaluate the spatial distribution of NPF events and their occurrence probability. We found difference in the horizontal spatial distribution of new particle source areas was connected to typical meteorological conditions. The horizontal extent of NPF reached to larger than 500 km at two sites, favoured by the fast transport of northwesterly air masses.
Huizheng Che, Bing Qi, Hujia Zhao, Xiangao Xia, Thomas F. Eck, Philippe Goloub, Oleg Dubovik, Victor Estelles, Emilio Cuevas-Agulló, Luc Blarel, Yunfei Wu, Jun Zhu, Rongguang Du, Yaqiang Wang, Hong Wang, Ke Gui, Jie Yu, Yu Zheng, Tianze Sun, Quanliang Chen, Guangyu Shi, and Xiaoye Zhang
Atmos. Chem. Phys., 18, 405–425, https://doi.org/10.5194/acp-18-405-2018, https://doi.org/10.5194/acp-18-405-2018, 2018
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Sun photometer measurements from seven sites in the Yangtze River Delta (YRD) from 2011 to 2015 were used to characterize the climatology of aerosol microphysical and optical properties, calculate direct aerosol radiative forcing (DARF) and classify aerosols based on size and absorption. This study contributes to our understanding of aerosols and regional climate/air quality, and the results will be useful for validating satellite retrievals and for improving climate models and remote sensing.
Junting Zhong, Xiaoye Zhang, Yunsheng Dong, Yaqiang Wang, Cheng Liu, Jizhi Wang, Yangmei Zhang, and Haochi Che
Atmos. Chem. Phys., 18, 247–258, https://doi.org/10.5194/acp-18-247-2018, https://doi.org/10.5194/acp-18-247-2018, 2018
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Beijing heavy pollution episodes are characterized by the transport stage (TS) and the cumulative stage (CS). PM2.5 pollution formation in the TS is primarily caused by pollutants transported from the south of Beijing. PM2.5 cumulative explosive growth in the CS is dominated by stable atmospheric stratification due to the interaction of particulate matter (PM) and meteorological factors. The positive meteorological feedback on PM2.5 mass noted explains over 70% of cumulative explosive growth.
Shurui Chen, Liang Xu, Yinxiao Zhang, Bing Chen, Xinfeng Wang, Xiaoye Zhang, Mei Zheng, Jianmin Chen, Wenxing Wang, Yele Sun, Pingqing Fu, Zifa Wang, and Weijun Li
Atmos. Chem. Phys., 17, 1259–1270, https://doi.org/10.5194/acp-17-1259-2017, https://doi.org/10.5194/acp-17-1259-2017, 2017
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Many studies have focused on the unusually severe hazes instead of the more frequent light and moderate hazes (22–63 %) in winter in the North China Plain (NCP). The morphology, mixing state, and size of organic aerosols in the L & M hazes were characterized. We conclude that the direct emissions from residential coal stoves without any pollution controls in rural and urban outskirts contribute large amounts of primary OM particles to the regional L & M hazes in winter in the NCP.
Y. Q. Yang, J. Z. Wang, S. L. Gong, X. Y. Zhang, H. Wang, Y. Q. Wang, J. Wang, D. Li, and J. P. Guo
Atmos. Chem. Phys., 16, 1353–1364, https://doi.org/10.5194/acp-16-1353-2016, https://doi.org/10.5194/acp-16-1353-2016, 2016
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A new model, PLAM/h, has been developed and used in near-real-time air quality forecasts by considering both meteorology and pollutant emissions, based on the two-dimensional probability density function diagnosis model for emissions. The results show that combining the influence of regular meteorological conditions and emission factors together in the PLAM/h parameterization scheme is very effective in improving the forecasting ability for fog-haze weather in North China.
P. Wang, H. Wang, Y. Q. Wang, X. Y. Zhang, S. L. Gong, M. Xue, C. H. Zhou, H. L. Liu, X. Q. An, T. Niu, and Y. L. Cheng
Atmos. Chem. Phys., 16, 989–1002, https://doi.org/10.5194/acp-16-989-2016, https://doi.org/10.5194/acp-16-989-2016, 2016
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An ensemble optimal interpolation (EnOI) data assimilation technique is used to investigate the possibility of optimally recovering the spatially resolved emissions bias of BC. The inversed emission over China in January is 240.1 Gg, and annual emission is about 2539 Gg. Even though only monthly mean BC measurements are employed to inverse the emissions, the accuracy of the daily model simulation improves. We finds that EnOI is a useful and computation-free method to make top-down estimation.
C. Zhou, X. Zhang, S. Gong, Y. Wang, and M. Xue
Atmos. Chem. Phys., 16, 145–160, https://doi.org/10.5194/acp-16-145-2016, https://doi.org/10.5194/acp-16-145-2016, 2016
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A comprehensive aerosol-cloud-precipitation interaction (ACI) scheme from emissions to precipitation has been developed under the CMA chemical weather modeling system GRAPES/CUACE. The ACI for January 2013 has been studied using this model. The interactive microphysical properties of clouds improve the precipitation, showing 24 to 48 % enhancements of threat score for 6 h precipitation in all regions and reduction of the regional mean bias of temperature by 3 °C in certain precipitation events.
Y. Q. Wang, X. Y. Zhang, J. Y. Sun, X. C. Zhang, H. Z. Che, and Y. Li
Atmos. Chem. Phys., 15, 13585–13598, https://doi.org/10.5194/acp-15-13585-2015, https://doi.org/10.5194/acp-15-13585-2015, 2015
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Concentrations of PM10, PM2.5 and PM1 were monitored at 24 stations of CAWNET from 2006 to 2014. The average levels of particulate matter (PM) concentrations and relationships were investigated. Seasonal, interannual and diurnal variations of the PM were revealed. The effects of meteorological factors on the PM were discussed. The highest PM concentrations were observed at the stations of Xian, Zhengzhou and Gucheng, in Guanzhong and the Huabei Plain.
X. Y. Zhang, J. Z. Wang, Y. Q. Wang, H. L. Liu, J. Y. Sun, and Y. M. Zhang
Atmos. Chem. Phys., 15, 12935–12952, https://doi.org/10.5194/acp-15-12935-2015, https://doi.org/10.5194/acp-15-12935-2015, 2015
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No obvious changes were found in annual mean concentrations of major chemical components and PM10 in 2013, relative to 2012. But wintertime mass were quite different; approximately 60% of the winter mass increase from 2012 to 2013 can be attributed to severe meteorological conditions in the HBP area, and mass of chemical components exhibited a decline during 2006 to 2010, and then a rise till 2013. Coal-combustion was still the largest anthropogenic source of aerosol pollution in 2013 in China.
J. W. Chi, W. J. Li, D. Z. Zhang, J. C. Zhang, Y. T. Lin, X. J. Shen, J. Y. Sun, J. M. Chen, X. Y. Zhang, Y. M. Zhang, and W. X. Wang
Atmos. Chem. Phys., 15, 11341–11353, https://doi.org/10.5194/acp-15-11341-2015, https://doi.org/10.5194/acp-15-11341-2015, 2015
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Sea salt aerosols (SSA) are dominant particles in the Arctic atmosphere. Our result suggests that the hydrophilic MgCl2 coating in fresh SSA likely intrigued the heterogeneous reactions at the beginning of SSA and acidic gases in the Arctic. The content of organic matter increased in the aged SSA compared with the fresh SSA, which suggests organic acids (beside inorganic acids) participate in the ageing of SSA in the Arctic.
L. Zhang, J. Y. Sun, X. J. Shen, Y. M. Zhang, H. Che, Q. L. Ma, Y. W. Zhang, X. Y. Zhang, and J. A. Ogren
Atmos. Chem. Phys., 15, 8439–8454, https://doi.org/10.5194/acp-15-8439-2015, https://doi.org/10.5194/acp-15-8439-2015, 2015
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The aerosol hygroscopic properties at a rural background site in the Yangtze River delta of China was discussed. The results show the scattering coefficient and backscattering coefficient increased by 58 and 25% as relative humidity (RH) increased from 40 to 85%, while the hemispheric backscatter fraction decreased by 21%. Aerosol hygroscopic growth caused a 47% increase in calculated aerosol direct radiative forcing at 85% RH compared to the forcing at 40% RH. Nitrate played a vital role.
H. Che, X.-Y. Zhang, X. Xia, P. Goloub, B. Holben, H. Zhao, Y. Wang, X.-C. Zhang, H. Wang, L. Blarel, B. Damiri, R. Zhang, X. Deng, Y. Ma, T. Wang, F. Geng, B. Qi, J. Zhu, J. Yu, Q. Chen, and G. Shi
Atmos. Chem. Phys., 15, 7619–7652, https://doi.org/10.5194/acp-15-7619-2015, https://doi.org/10.5194/acp-15-7619-2015, 2015
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This work studied more than 10 years of measurements of aerosol optical depths (AODs) made for 50 sites of CARSNET compiled into a climatology of aerosol optical properties for China. It lets us see a detailed full-scale description of AOD observations over China. The results would benefit us a lot in comprehending the temporal and special distribution aerosol optical property over China. Also the data would be valuable to communities of aerosol satellite retrieval, modelling, etc.
Z. L. Wang, H. Zhang, and X. Y. Zhang
Atmos. Chem. Phys., 15, 3671–3685, https://doi.org/10.5194/acp-15-3671-2015, https://doi.org/10.5194/acp-15-3671-2015, 2015
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This study highlights that there are no effective ways to remove the black carbon exclusively without influencing the other co-emitted components, our results therefore indicate that a reduction in BC emission can lead to an unexpected warming on the Earth’s climate system in the future.
H. Wang, M. Xue, X. Y. Zhang, H. L. Liu, C. H. Zhou, S. C. Tan, H. Z. Che, B. Chen, and T. Li
Atmos. Chem. Phys., 15, 3257–3275, https://doi.org/10.5194/acp-15-3257-2015, https://doi.org/10.5194/acp-15-3257-2015, 2015
H. Wang, G. Y. Shi, X. Y. Zhang, S. L. Gong, S. C. Tan, B. Chen, H. Z. Che, and T. Li
Atmos. Chem. Phys., 15, 3277–3287, https://doi.org/10.5194/acp-15-3277-2015, https://doi.org/10.5194/acp-15-3277-2015, 2015
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Solar radiation reaching the ground decreases about 15% in Chinese 3JNS region and by 20 to 25% in the region with the highest AOD. Aerosol cools the PBL atmosphere but warms the atmosphere above it, leading to a more stable atmosphere that causes a decrease in turbulence diffusion of about 52% and in PBL height of about 33%; this results in a positive feedback on the PM2.5 concentration within the PBL and the surface as well as the haze formation.
Y. M. Zhang, X. Y. Zhang, J. Y. Sun, G. Y. Hu, X. J. Shen, Y. Q. Wang, T. T. Wang, D. Z. Wang, and Y. Zhao
Atmos. Chem. Phys., 14, 12237–12249, https://doi.org/10.5194/acp-14-12237-2014, https://doi.org/10.5194/acp-14-12237-2014, 2014
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An AMS was employed to measure the mass and size distributions of PM1 at an elevated site. Features of PM1 at four seasons, during different kinds of episodes including NPF, polluted, PBL, LFT and in-cloud, were discussed. The characterizations of PM1 at seven clusters of air masses were also analyzed. BBOA, CCOA and oxidized organic aerosols were resolved by AMS-PMF (positive matrix function). Almost half of OA were oxidized, and BBOA is 34% of OA in summer; CCOA is 22% of OA in winter as well.
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell, S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, and X. Zhang
Atmos. Chem. Phys., 14, 10845–10895, https://doi.org/10.5194/acp-14-10845-2014, https://doi.org/10.5194/acp-14-10845-2014, 2014
H. Che, X. Xia, J. Zhu, Z. Li, O. Dubovik, B. Holben, P. Goloub, H. Chen, V. Estelles, E. Cuevas-Agulló, L. Blarel, H. Wang, H. Zhao, X. Zhang, Y. Wang, J. Sun, R. Tao, X. Zhang, and G. Shi
Atmos. Chem. Phys., 14, 2125–2138, https://doi.org/10.5194/acp-14-2125-2014, https://doi.org/10.5194/acp-14-2125-2014, 2014
A. Petzold, J. A. Ogren, M. Fiebig, P. Laj, S.-M. Li, U. Baltensperger, T. Holzer-Popp, S. Kinne, G. Pappalardo, N. Sugimoto, C. Wehrli, A. Wiedensohler, and X.-Y. Zhang
Atmos. Chem. Phys., 13, 8365–8379, https://doi.org/10.5194/acp-13-8365-2013, https://doi.org/10.5194/acp-13-8365-2013, 2013
H. Jiang, H. Liao, H. O. T. Pye, S. Wu, L. J. Mickley, J. H. Seinfeld, and X. Y. Zhang
Atmos. Chem. Phys., 13, 7937–7960, https://doi.org/10.5194/acp-13-7937-2013, https://doi.org/10.5194/acp-13-7937-2013, 2013
Related subject area
Atmospheric sciences
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Modelling extensive green roof CO2 exchanges in the TEB urban canopy model
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 2: livestock farming
Least travel time ray tracer, version Two (LTT v2) adapted to the grid geometry of the OpenIFS atmospheric model
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Aurélien Mirebeau, Cécile de Munck, Bertrand Bonan, Christine Delire, Aude Lemonsu, Valéry Masson, and Stephan Weber
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-233, https://doi.org/10.5194/gmd-2024-233, 2025
Revised manuscript accepted for GMD
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The greening of cities is recommended to limit the effects of climate change. In particular, green roofs can provide numerous environmental benefits, such as urban cooling, water retention and carbon sequestration. The aim of this research is to develop a new module for calculating green roof CO2 fluxes within a model that can already simulate hydrological and thermal processes of such roofs. The calibration and evaluation of this module take advantage of long term experimental data.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
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We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Jize Jiang, David S. Stevenson, Aimable Uwizeye, Giuseppe Tempio, Alessandra Falcucci, Flavia Casu, and Mark A. Sutton
EGUsphere, https://doi.org/10.5194/egusphere-2024-3803, https://doi.org/10.5194/egusphere-2024-3803, 2024
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A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from livestock farming. It is estimated that about 30 % of excreted N from livestock was lost due to NH3 emissions from housing, manure management and land application of manure. High NH3 volatilization often occurred in hot regions, while poor management practices also result in significant N losses through NH3 emissions.
Maksym Vasiuta, Angel Navarro Trastoy, Sanam Motlaghzadeh, Lauri Tuppi, Torsten Mayer-Gürr, and Heikki Järvinen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-136, https://doi.org/10.5194/gmd-2024-136, 2024
Revised manuscript accepted for GMD
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Propagation of electromagnetic signals in the Earth's neutral atmosphere inflicts errors in space geodetic observations. To model these errors as accurately as possible, it is necessary to use a signal ray tracing algorithm which is informed of the state of the atmosphere. We developed such algorithm and tested it by modelling errors in GNSS network observations. Our algorithm's main advantage is loss-less utilization of atmospheric information provided by numerical weather prediction models.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
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We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
Cited articles
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Chang, P., Zhang, S., Danabasoglu, G., Yeager, S. G., Fu, H., Wang, H., Castruccio, F. S., Chen, Y., Edwards, J., Fu, D., Jia, Y., Laurindo, L. C., Liu, X., Rosenbloom, N., Small, R. J., Xu, G., Zeng, Y., Zhang, Q., Bacmeister, J., Bailey, D. A., Duan, X., DuVivier, A. K., Li, D., Li, Y., Neale, R., Stössel, A., Wang, L., Zhuang, Y., Baker, A., Bates, S., Dennis, J., Diao, X., Gan, B., Gopal, A., Jia, D., Jing, Z., Ma, X., Saravanan, R., Strand, W. G., Tao, J., Yang, H., Wang, X., Wei, Z., and Wu, L.: An Unprecedented Set of High-Resolution Earth System Simulations for Understanding Multiscale Interactions in Climate Variability and Change, J. Adv. Model. Earth Sy., 12, e2020MS002298, https://doi.org/10.1029/2020MS002298, 2020.
Friedl, M. A., McIver, D. K., Hodges, J. C. F., Zhang, X. Y., Muchoney, D., Strahler, A. H., Woodcock, C. E., Gopal, S., Schneider, A., Cooper, A., Baccini, A., Gao, F., and Schaaf, C.: Global land cover mapping from MODIS: algorithms and early results, Remote Sens. Environ., 83, 287–302, https://doi.org/10.1016/S0034-4257(02)00078-0, 2002.
García-García, A., Cuesta-Valero, F. J., Beltrami, H., González-Rouco, J. F., and García-Bustamante, E.: WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America, Geosci. Model Dev., 15, 413–428, https://doi.org/10.5194/gmd-15-413-2022, 2022.
Jia, W. and Zhang, X.: The role of the planetary boundary layer parameterization schemes on the meteorological and aerosol pollution simulations: A review, Atmos. Res., 239, 104890, https://doi.org/10.1016/j.atmosres.2020.104890, 2020.
Jia, W., Zhang, X., Wang, H., Wang, Y., Wang, D., Zhong, J., Zhang, W., Zhang, L., Guo, L., Lei, Y., Wang, J., Yang, Y., and Lin, Y.: Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 1: Understanding expressiveness of schemes for different regions from the mechanism perspective, Geosci. Model Dev., 16, 6635–6670, https://doi.org/10.5194/gmd-16-6635-2023, 2023.
Li, D., Chang, P., Yeager, S. G., Danabasoglu, G., Castruccio, F. S., Small, J., Wang, H., Zhang, Q., and Gopal, A.: The Impact of Horizontal Resolution on Projected Sea-Level Rise Along US East Continental Shelf With the Community Earth System Model, J. Adv. Model. Earth Sy., 14, e2021MS002868, https://doi.org/10.1029/2021MS002868, 2022.
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Li, Y., Gao, Z., Lenschow, D. H., and Chen, F.: An Improved Approach for Parameterizing Surface-Layer Turbulent Transfer Coefficients in Numerical Models, Bound.-Lay. Meteorol., 137, 153–165, https://doi.org/10.1007/s10546-010-9523-y, 2010.
Ma, Z., Liu, Q., Zhao, C., Shen, X., Wang, Y., Jiang, J. H., Li, Z., and Yung, Y.: Application and Evaluation of an Explicit Prognostic Cloud-Cover Scheme in GRAPES Global Forecast System, J. Adv. Model. Earth Sy., 10, 652–667, https://doi.org/10.1002/2017MS001234, 2018.
Ma, Z., Zhao, C., Gong, J., Zhang, J., Li, Z., Sun, J., Liu, Y., Chen, J., and Jiang, Q.: Spin-up characteristics with three types of initial fields and the restart effects on forecast accuracy in the GRAPES global forecast system, Geosci. Model Dev., 14, 205–221, https://doi.org/10.5194/gmd-14-205-2021, 2021.
Magnusson, L. and Källén, E.: Factors Influencing Skill Improvements in the ECMWF Forecasting System, Mon. Weather Rev., 141, 3142–3153, https://doi.org/10.1175/mwr-d-12-00318.1, 2013.
Menut, L., Bessagnet, B., Colette, A., and Khvorostiyanov, D.: On the impact of the vertical resolution on chemistry-transport modelling, Atmos. Environ., 67, 370–384, https://doi.org/10.1016/j.atmosenv.2012.11.026, 2013.
Morichetti, M., Madronich, S., Passerini, G., Rizza, U., Mancinelli, E., Virgili, S., and Barth, M.: Comparison and evaluation of updates to WRF-Chem (v3.9) biogenic emissions using MEGAN, Geosci. Model Dev., 15, 6311–6339, https://doi.org/10.5194/gmd-15-6311-2022, 2022.
National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce: NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, https://doi.org/10.5065/D6M043C6, 2000 (updated daily).
National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce: NCEP GDAS/FNL 0.25 Degree Global Tropospheric Analyses and Forecast Grids, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, https://doi.org/10.5065/D65Q4T4Z, 2015 (updated daily).
Nolan, D. S. and Onderlinde, M. J.: The Representation of Spiral Gravity Waves in a Mesoscale Model With Increasing Horizontal and Vertical Resolution, J. Adv. Model. Earth Sy., 14, e2022MS002989, https://doi.org/10.1029/2022MS002989, 2022.
O'Dea, E., Furner, R., Wakelin, S., Siddorn, J., While, J., Sykes, P., King, R., Holt, J., and Hewitt, H.: The CO5 configuration of the 7 km Atlantic Margin Model: large-scale biases and sensitivity to forcing, physics options and vertical resolution, Geosci. Model Dev., 10, 2947–2969, https://doi.org/10.5194/gmd-10-2947-2017, 2017.
Ouyang, Z., Sciusco, P., Jiao, T., Feron, S., Lei, C., Li, F., John, R., Fan, P., Li, X., Williams, C. A., Chen, G., Wang, C., and Chen, J.: Albedo changes caused by future urbanization contribute to global warming, Nat. Commun., 13, 3800, https://doi.org/10.1038/s41467-022-31558-z, 2022.
Qian, Y., Chakraborty, T. C., Li, J., Li, D., He, C., Sarangi, C., Chen, F., Yang, X., and Leung, L. R.: Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions, Adv. Atmos. Sci., 39, 819–860, https://doi.org/10.1007/s00376-021-1371-9, 2022.
Roberts, M. J., Jackson, L. C., Roberts, C. D., Meccia, V., Docquier, D., Koenigk, T., Ortega, P., Moreno-Chamarro, E., Bellucci, A., Coward, A., Drijfhout, S., Exarchou, E., Gutjahr, O., Hewitt, H., Iovino, D., Lohmann, K., Putrasahan, D., Schiemann, R., Seddon, J., Terray, L., Xu, X., Zhang, Q., Chang, P., Yeager, S. G., Castruccio, F. S., Zhang, S., and Wu, L.: Sensitivity of the Atlantic Meridional Overturning Circulation to Model Resolution in CMIP6 HighResMIP Simulations and Implications for Future Changes, J. Adv. Model. Earth Sy., 12, e2019MS002014, https://doi.org/10.1029/2019MS002014, 2020.
Rummukainen, M.: Added value in regional climate modeling, WIREs Climate Change, 7, 145–159, https://doi.org/10.1002/wcc.378, 2016.
Schwaab, J., Meier, R., Mussetti, G., Seneviratne, S., Bürgi, C., and Davin, E. L.: The role of urban trees in reducing land surface temperatures in European cities, Nat. Commun., 12, 6763, https://doi.org/10.1038/s41467-021-26768-w, 2021.
Singh, J., Singh, N., Ojha, N., Sharma, A., Pozzer, A., Kiran Kumar, N., Rajeev, K., Gunthe, S. S., and Kotamarthi, V. R.: Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya, Geosci. Model Dev., 14, 1427–1443, https://doi.org/10.5194/gmd-14-1427-2021, 2021.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D., Duda, M. G., and Powers, J. G.: A Description of the Advanced Research WRF Version 3 (No. NCAR/TN475+STR), University Corporation for Atmospheric Research, https://doi.org/10.5065/D68S4MVH, 2008 (data available at: https://www2.mmm.ucar.edu/wrf/users/download/ last access: 22 November 2023).
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Tolentino, J., Rejuso, M. V., Inocencio, L. C., Ang, M. R. C., and Bagtasa, G.: Effect of horizontal and vertical resolution for wind resource assessment in Metro Manila, Philippines using Weather Research and Forecasting (WRF) model, Vol. 10005, SPIE, https://doi.org/10.1117/12.2241952, 2016.
Wang, L. and Li, D.: Urban Heat Islands during Heat Waves: A Comparative Study between Boston and Phoenix, J. Appl. Meteorol. Clim., 60, 621–641, https://doi.org/10.1175/JAMC-D-20-0132.1, 2021.
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Zhou, B., Zhu, K., and Xue, M.: A Physically Based Horizontal Subgrid-Scale Turbulent Mixing Parameterization for the Convective Boundary Layer, J. Atmos.Sci., 74, 2657–2674, https://doi.org/10.1175/jas-d-16-0324.1, 2017.
Short summary
In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
In addition to the dominant role of the PBL scheme on the results of the meteorological field,...
